Glycan-protein interactions determine kinetics of N-glycan remodeling

Restoring protein glycosylation with GlycoShape

Despite ground-breaking innovations in experimental structural biology and protein structure prediction techniques, capturing the structure of the glycans that functionalize proteins remains a challenge. Here we introduce GlycoShape ( https://glycoshape.org ), an open-access glycan structure database and toolbox designed to restore glycoproteins to their native and functional form in seconds. The GlycoShape database counts over 500 unique glycans so far, covering the human glycome and augmented by elements from a wide range of organisms, obtained from 1 ms of cumulative sampling from molecular dynamics simulations. These structures can be linked to proteins with a robust algorithm named Re-Glyco, directly compatible with structural data in open-access repositories, such as the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and AlphaFold Protein Structure Database, or own. The quality, performance and broad applicability of GlycoShape is demonstrated by its ability to predict N-glycosylation occupancy, scoring a 93% agreement with experiment, based on screening all proteins in the PDB with a corresponding glycoproteomics profile, for a total of 4,259 N-glycosylation sequons.

A hierarchical structure in the N-glycosylation process governs the N-glycosylation output: prolonged cultivation induces glycoenzymes expression variations that are reflected in the cellular N-glycome but not in the protein and site-specific glycoprofile of CHO cells

N-glycosylation is a central component in the modification of secretory proteins. One characteristic of this process is a heterogeneous output. The heterogeneity is the result of both structural constraints of the glycoprotein as well as the composition of the cellular glycosylation machinery. Empirical data addressing correlations between glycosylation output and glycosylation machinery composition are seldom due to the low abundance of glycoenzymes. We assessed how differences in the glycoenzyme expression affected the N-glycosylation output at a cellular as well as at a protein-specific level. Our results showed that cellular N-glycome changes could be correlated with the variation of glycoenzyme expression, whereas at the protein level differential responses to glycoenzymes alterations were observed. We therefore identified a hierarchical structure in the N-glycosylation process: the enzyme levels in this complex pathway determine its capacity (reflected in the N-glycome), while protein-specific parameters determine the glycosite-specificity. What emerges is a highly variable and adaptable protein modification system that represents a hallmark of eukaryotic cells.

Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network

Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.

Systematic Investigation of the Trafficking of Glycoproteins on the Cell Surface

Glycoproteins located on the cell surface play a pivotal role in nearly every extracellular activity. N-glycosylation is one of the most common and important protein modifications in eukaryotic cells, and it often regulates protein folding and trafficking. Glycosylation of cell-surface proteins undergoes meticulous regulation by various enzymes in the endoplasmic reticulum (ER) and the Golgi, ensuring their proper folding and trafficking to the cell surface. However, the impacts of protein N-glycosylation, N-glycan maturity, and protein folding status on the trafficking of cell-surface glycoproteins remain to be explored. In this work, we comprehensively and site-specifically studied the trafficking of cell-surface glycoproteins in human cells. Integrating metabolic labeling, bioorthogonal chemistry, and multiplexed proteomics, we investigated 706 N-glycosylation sites on 396 cell-surface glycoproteins in monocytes, either by inhibiting protein N-glycosylation, disturbing N-glycan maturation, or perturbing protein folding in the ER. The current results reveal their distinct impacts on the trafficking of surface glycoproteins. The inhibition of protein N-glycosylation dramatically suppresses the trafficking of many cell-surface glycoproteins. The N-glycan immaturity has more substantial effects on proteins with high N-glycosylation site densities, while the perturbation of protein folding in the ER exerts a more pronounced impact on surface glycoproteins with larger sizes. Furthermore, for N-glycosylated proteins, their trafficking to the cell surface is related to the secondary structures and adjacent amino acid residues of glycosylation sites. Systematic analysis of surface glycoprotein trafficking advances our understanding of the mechanisms underlying protein secretion and surface presentation.

Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries

Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins. Computer simulations may be used to model glycosylated proteins but require hundreds of thousands of computing hours on supercomputers, thus limiting routine use. Here, we describe GlycoSHIELD, a reductionist method that can be implemented on personal computers to graft realistic ensembles of glycan conformers onto static protein structures in minutes. Using molecular dynamics simulation, small-angle X-ray scattering, cryoelectron microscopy, and mass spectrometry, we show that this open-access toolkit provides enhanced models of glycoprotein structures. Focusing on N-cadherin, human coronavirus spike proteins, and gamma-aminobutyric acid receptors, we show that GlycoSHIELD can shed light on the impact of glycans on the conformation and activity of complex glycoproteins.

CommonNNClustering─A Python Package for Generic Common-Nearest-Neighbor Clustering

Density-based clustering procedures are widely used in a variety of data science applications. Their advantage lies in the capability to find arbitrarily shaped and sized clusters and robustness against outliers. In particular, they proved effective in the analysis of molecular dynamics simulations, where they serve to identify relevant, low-energetic molecular conformations. As such, they can provide a convenient basis for the construction of kinetic (core-set) Markov-state models. Here we present the open-source Python project CommonNNClustering, which provides an easy-to-use and efficient reimplementation of the common-nearest-neighbor (CommonNN) method. The package provides functionalities for hierarchical clustering and an evaluation of the results. We put our emphasis on a generic API design to keep the implementation flexible and open for customization.

Sequential in vitro enzymatic N-glycoprotein modification reveals site-specific rates of glycoenzyme processing

N-glycosylation is an essential eukaryotic posttranslational modification that affects various glycoprotein properties, including folding, solubility, protein–protein interactions, and half-life. N-glycans are processed in the secretory pathway to form varied ensembles of structures, and diversity at a single site on a glycoprotein is termed ‘microheterogeneity’. To understand the factors that influence glycan microheterogeneity, we hypothesized that local steric and electrostatic factors surrounding each site influence glycan availability for enzymatic modification. We tested this hypothesis via expression of reporter N-linked glycoproteins in N-acetylglucosaminyltransferase MGAT1-null HEK293 cells to produce immature Man₅GlcNAc₂ glycoforms (38 glycan sites total). These glycoproteins were then sequentially modified in vitro from high mannose to hybrid and on to biantennary, core-fucosylated, complex structures by a panel of N-glycosylation enzymes, and each reaction time course was quantified by LC-MS/MS. Substantial differences in rates of in vitro enzymatic modification were observed between glycan sites on the same protein, and differences in modification rates varied depending on the glycoenzyme being evaluated. In comparison, proteolytic digestion of the reporters prior to N-glycan processing eliminated differences in in vitro enzymatic modification. Furthermore, comparison of in vitro rates of enzymatic modification with the glycan structures found on the mature reporters expressed in WT cells correlated well with the enzymatic bottlenecks observed in vivo. These data suggest higher order local structures surrounding each glycosylation site contribute to the efficiency of modification both in vitro and in vivo to establish the spectrum of microheterogeneity in N-linked glycoproteins.

Native glycosylation and binding of the antidepressant paroxetine in a low-resolution crystal structure of human myeloperoxidase

Human myeloperoxidase (MPO) utilizes hydrogen peroxide to oxidize organic compounds and as such plays an essential role in cell-component synthesis, in metabolic and elimination pathways, and in the front-line defence against pathogens. Moreover, MPO is increasingly being reported to play a role in inflammation. The enzymatic activity of MPO has also been shown to depend on its glycosylation. Mammalian MPO crystal structures deposited in the Protein Data Bank (PDB) present only a partial identification of their glycosylation. Here, a newly obtained crystal structure of MPO containing four disulfide-linked dimers and showing an elaborate collection of glycans is reported. These are compared with the glycans identified in proteomics studies and from 18 human MPO structures available in the PDB. The crystal structure also contains bound paroxetine, a blocker of serotonin reuptake that has previously been identified as an irreversible inhibitor of MPO, in the presence of thiocyanate, a physiological substrate of MPO.

N-glycosylation modulates enzymatic activity of Trypanosoma congolense trans-sialidase

Trypanosomes cause the devastating disease trypanosomiasis, in which the action of trans-sialidase (TS) enzymes harbored on their surface is a key virulence factor. TS enzymes are N-glycosylated, but the biological functions of their glycans have remained elusive. In this study, we investigated the influence of N-glycans on the enzymatic activity and structural stability of TconTS1, a recombinant TS from the African parasite Trypanosoma congolense. We expressed the enzyme in Chinese hamster ovary Lec1 cells, which produce high-mannose type N-glycans similar to the TS N-glycosylation pattern in vivo. Our MALDI-TOF mass spectrometry data revealed that up to eight putative N-glycosylation sites were glycosylated. In addition, we determined that N-glycan removal via endoglycosidase H_f treatment of TconTS1 led to a decrease in substrate affinity relative to the untreated enzyme but had no impact on the conversion rate. Furthermore, we observed no changes in secondary structure elements of hypoglycosylated TconTS1 in CD experiments. Finally, our molecular dynamics simulations provided evidence for interactions between monosaccharide units of the highly flexible N-glycans and some conserved amino acids located at the catalytic site. These interactions led to conformational changes, possibly enhancing substrate accessibility and enzyme–substrate complex stability. The here-observed modulation of catalytic activity via N-glycans represents a so-far-unknown structure–function relationship potentially inherent in several members of the TS enzyme family.

Unusual β1-4-galactosidase activity of an α1-6-mannosidase from Xanthomonas manihotis in the processing of branched hybrid and complex glycans

Mannosidases are a diverse group of glycoside hydrolases that play crucial roles in mannose trimming of oligomannose glycans, glycoconjugates, and glycoproteins involved in numerous cellular processes, such as glycan biosynthesis and metabolism, structure regulation, cellular recognition, and cell–pathogen interactions. Exomannosidases and endomannosidases cleave specific glycosidic bonds of mannoside linkages in glycans and can be used in enzyme-based methods for sequencing of isomeric glycan structures. α1-6-mannosidase from Xanthomonas manihotis is known as a highly specific exoglycosidase that removes unbranched α1-6 linked mannose residues from oligosaccharides. However, we discovered that this α1-6-mannosidase also possesses an unexpected β1-4-galactosidase activity in the processing of branched hybrid and complex glycans through our use of enzymatic reactions, high performance anion-exchange chromatography, and liquid chromatography mass spectrometric sequencing. Our docking simulation of the α1-6-mannosidase with glycan substrates reveals potential interacting residues in a relatively shallow pocket slightly differing from its homologous enzymes in the glycoside hydrolase 125 family, which may be responsible for the observed higher promiscuity in substrate binding and subsequent terminal glycan hydrolysis. This observation of novel β1-4-galactosidase activity of the α1-6-mannosidase provides unique insights into its bifunctional activity on the substrate structure-dependent processing of terminal α1-6-mannose of unbranched glycans and terminal β1-4-galactose of hybrid and complex glycans. The finding thus suggests the dual glycosidase specificity of this α1-6-mannosidase and the need for careful consideration when used for the structural elucidation of glycan isomers.

Molecular simulations of complex carbohydrates and glycoconjugates

Complex carbohydrates (glycans) are the most abundant and versatile biopolymers in nature. The broad diversity of biochemical functions that carbohydrates cover is a direct consequence of the variety of 3D architectures they can adopt, displaying branched or linear arrangements, widely ranging in sizes, and with the highest diversity of building blocks of any other natural biopolymer. Despite this unparalleled complexity, a common denominator can be found in the glycans' inherent flexibility, which hinders experimental characterization, but that can be addressed by high-performance computing (HPC)-based molecular simulations. In this short review, I present and discuss the state-of-the-art of molecular simulations of complex carbohydrates and glycoconjugates, highlighting methodological strengths and weaknesses, important insights through emblematic case studies, and suggesting perspectives for future developments.

Principles of SARS-CoV-2 Glycosylation

The structure and post-translational processing of the SARS-CoV-2 spike glycoprotein (S) is intimately associated with the function of the virus and of sterilising vaccines. The surface of the S protein is extensively modified by glycans, and their biosynthesis is driven by both the wider cellular context, and importantly, the underlining protein structure and local glycan density. Comparison of virally derived S protein with both recombinantly derived and adenovirally induced proteins, reveal hotspots of protein-directed glycosylation that drive conserved glycosylation motifs. Molecular dynamics simulations revealed that, while the S surface is extensively shielded by N-glycans, it presents regions vulnerable to neutralising antibodies. Furthermore, glycans have been shown to influence the accessibility of the receptor binding domain and the binding to the cellular receptor. The emerging picture is one of unifying, principles of S protein glycosylation and an intimate role of glycosylation in immunogen structure and efficacy.

Site-specific N-glycan profiles of α5 β1 integrin from rat liver

BACKGROUND INFORMATION

Like most other cell surface proteins, α₅ β₁ integrin is glycosylated, which is required for its various activities in ways that mostly remain to be determined.

RESULTS

Here, we have established the first comprehensive site-specific glycan map of α₅ β₁ integrin that was purified from a natural source, i.e., rat liver. This analysis revealed striking site selective variations in glycan composition. Complex bi, tri or tetraantennary N-glycans were predominant at various proportions at most potential N-glycosylation sites. A few of these sites were non-glycosylated or contained high mannose or hybrid glycans, indicating that early N-glycan processing was hindered. Almost all complex N-glycans had fully galactosylated and sialylated antennae. Moderate levels of core fucosylation and high levels of O-acetylation of NeuAc residues were observed at certain sites. An O-linked HexNAc was found in an EGF-like domain of β₁ integrin. The extensive glycan information that results from our study was projected onto a map of α₅ β₁ integrin that was obtained by homology modeling. We have used this model for the discussion of how glycosylation might be used in the functional cycle of α₅ β₁ integrin. A striking example concerns the involvement of glycan-binding galectins in the regulation of the molecular homeostasis of glycoproteins at the cell surface through the formation of lattices or endocytic pits according to the glycolipid-lectin (GL-Lect) hypothesis.

CONCLUSION

We expect that the glycoproteomics data of the current study will serve as a resource for the exploration of structural mechanisms by which glycans control α₅ β₁ integrin activity and endocytic trafficking.

SIGNIFICANCE

Glycosylation of α₅ β₁ integrin has been implicated in multiple aspects of integrin function and structure. Yet, detailed knowledge of its glycosylation, notably the specific sites of glycosylation, is lacking. Furthermore, the α₅ β₁ integrin preparation that was analyzed here is from a natural source, which is of importance as there is not a lot of literature in the field about the glycosylation of 'native' glycoproteins. This article is protected by copyright. All rights reserved.

N-Glycosylation Enhances Conformational Flexibility of Protein Disulfide Isomerase Revealed by Microsecond Molecular Dynamics and Markov State Modeling

Secreted proteins of eukaryotes are decorated with branched carbohydrate oligomers called glycans. This fact is only starting to be considered for in silico investigations of protein dynamics. Using all-atom molecular dynamics (MD) simulations and Markov state modeling (MSM), we unveil the influence of glycans on the conformational flexibility of the multidomain protein disulfide isomerase (PDI), which is a ubiquitous chaperone in the endoplasmic reticulum (ER). Yeast PDI (yPDI) from Saccharomyces cerevisiae is glycosylated at asparagine side chains and the knowledge of its five modified sites enables a realistic computational modeling. We compare simulations of glycosylated and unglycosylated yPDI and find that the presence of glycan-glycan and glycan-protein interactions influences the flexibility of PDI in different ways. For example, glycosylation reduces interdomain interactions, shifting the conformational ensemble toward more open, extended structures. In addition, we compare our results on yPDI with structural information of homologous proteins such as human PDI (hPDI), which is natively unglycosylated. Interestingly, hPDI lacks a surface recess that is present in yPDI. We find that glycosylation of yPDI facilitates its catalytic site to reach close to this surface recess. Hence, this might point to a possible functional relevance of glycosylation in yeast to act on substrates, while glycosylation seems redundant for the human homologous protein. We conclude that glycosylation is fundamental for protein dynamics, making it a necessity for a truthful representation of the flexibility and function in in silico studies of glycoproteins.